One variation of the method for managing blood loss of a patient includes: receiving an image of a physical sample; extracting a feature from an area of the image corresponding to the physical sample; estimating a blood volume indicator of the physical sample according to the extracted feature; estimating a patient blood loss based on the blood volume indicator; estimating a euvolemic patient hematocrit based on an estimated patient blood volume and the estimated patient blood loss; receiving a measured patient hematocrit; and generating a volemic status indicator based on a comparison between the measured patient hematocrit and the estimated euvolemic patient hematocrit.

The apparati, methods, and computer program products disclosed herein can be used to nondestructively detect undissolved particles, such as glass flakes and/or protein aggregates, in a fluid in a vessel, such as, but not limited to, a fluid that contains a drug.

Techniques for identifying and enumerating candidate target cells within a biological fluid specimen are described. A digital image of the biological fluid specimen is received, and one or more candidate regions of pixels in the digital image are identified by identifying connected regions of pixels of a minimum intensity having a size between a minimum size and a maximum size and an aspect ratio that meets a threshold. For each candidate region of at least one of the one or more candidate region, whether the portion of the image corresponding to the candidate region includes more than a threshold number of intensity levels is determined. If the portion of the image corresponding to the candidate region includes more than the threshold number of intensity levels the portion of the image is continued to be treated as a candidate for classification.

A method for identifying candidate target cells within a biological fluid specimen includes a digital image of the biological fluid specimen with the digital image having a plurality of color channels, identifying first connected regions of pixels of a minimum first intensity in a first channel, identifying second connected regions of pixels of a minimum second intensity in a second channel, and determining first connected regions and second connected regions that spatially overlap. For a pair of a first connected region and a second connected region that spatially overlap, whether the second connected region overlaps the first connected region by a threshold amount is determined, and if the second connected region overlaps the first connected region by the threshold amount then the portion of the image corresponding to the overlap is continued to be treated as a candidate for classification.

A method for identifying and enumerating candidate target cells within a biological fluid specimen is described. The method includes obtaining a biological fluid specimen, preparing the biological fluid specimen by staining cell features in the biological fluid specimen, capturing a digital image having a plurality of color channels of the biological fluid specimen, and applying image analysis to the digital image. A computer program product for identifying candidate target cells within a biological fluid specimen is also described. The computer program comprises instructions to cause a processor to carry out the image analysis.

A method for optically detecting biomarkers in a biosensor, comprising: simultaneously acquiring (1100) spatially and spectrally resolved images from at least one sample of the biosensor and performing an image analysis (1000) in parallel to the image acquisition (1100); wherein the image analysis (1000) comprises: reading (2100) data of the acquired images; correcting (2200) the data to reduce inhomogeneities and noise of the images; localizing (2300) particles in the images using the corrected data; characterizing (2400) each particle individually to obtain at least its position and characterization parameters; classifying (2500) the particles based on their characterization parameters to obtain particle classes; counting (2600) the particles for each class and acquired image; for each biomarker in each sample, calculating an overall analysis result (2800) comprising calculating at least one statistical value by using the number of particles per class for all the images acquired from the same sample, and the statistical value per sample being correlated with the presence of a biomarker in the sample.

Biosensing platform for simultaneous, multiplexed, high throughput and ultra-sensitive optical detection of biomarkers labelled with plasmonic nanoparticles, the platform being provided with a biosensor, a broadband and continuous spectrum illumination source, an optical detector for simultaneously capturing spatially resolved and spectrally resolved the scattering signal of each individual nanoparticle, an autofocus system and an optical system adapted to collect the scattered signal of the biosensor's surface onto the optical detector, the platform being provided with translation means for the optical system and/or the biosensor, such that the optical system and the biosensor can be displaced relative to each other in the three dimensions, and wherein the processing means are adapted to: i) simultaneously capture spatially and spectrally resolved scattering signals from each nanoparticle individually, and ii) to analyze these signals simultaneously with the capture process.

Among other things, an imaging sensor includes a two-dimensional array of photosensitive elements and a surface to receive a sample within a near-field distance of the photosensitive elements. Electronics classify microbeads in the sample as belonging to different classes based on the effects of different absorption spectra of the different classes of microbeads on light received at the surface. In some examples, the number of different distinguishable classes of microbeads can be very large based on combinations of the effects on light received at the surface of the different absorption spectra together, spatial arrangements of colorants in the microbeads that impart the different absorption spectra, different sizes of microbeads, and different shapes of microbeads, among other things.

A particle imaging device comprises a flow cell, a light source, an irradiation optical system configured to form a light sheet on the flow cell, a light collecting optical system and an imaging element. The sheet surface of the light sheet is perpendicular to the exterior side surface of the flow cell to which the light is entered from the light source. The sheet surface of the light sheet is inclined at a predetermined angle that is not perpendicular to the flow direction of the sample.

A method of treating a disease in a subject including: obtaining a blood sample from the subject, identifying and counting white blood cells in the blood sample, binding antibodies to cluster of differentiation (CD) markers on the white blood cells, capturing images of the white blood cells, detecting binding of the antibodies to the white blood cell based on labeling of the white blood cells in the images, and classifying the white blood cells into CD subgroups based on the CD markers, calculating a total number of white blood cells serving as immune cells in a body of the subject and a number of white blood cells in each immune cell CD subgroup based on the number of white blood cells counted and the CD classification, and determining an immune status of the subject based on a ratio of the immune cell subgroups and a number of cells in each of the immune cell subgroups by comparing to a corresponding ratio and corresponding numbers of cells in a normal subject, wherein a change compared to the normal subject indicates an increase or a decrease in the immune status; initiating or continuing treatment of the cancer in the subject, wherein the treatment is selected from the group consisting of medication and immunotherapy; and adjusting the treatment based on a change in the determined immune status.